leommoore

#SOA Manifesto

In 2002, Jeff Bezos (CEO of Amazon), issued a mandate requiring all teams to expose their data and functionality through services interfaces. Jeff Bezos understood that in order for his company to be successful, he had to switch focus from creating a "perfect product" to creating a perfect platform for that product.

He mandated that:

• All teams will henceforth expose their data and functionality through service interfaces
• Teams must communicate with each other through these interfaces
• There will be no other form of interprocess communication allowed: no direct linking, no direct reads of another team's data store, no shared-memory model, no back-doors whatsoever. The only communication is via service interface calls over the network.
• It doesn't matter what [API protocol] technology you use

shajra

import concurrent.{ExecutionContext, Future => SFuture, Promise}                 
import util.Try                                                                                                 
                                                                                                                
import _root_.scalaz.\/                                                                                         
import _root_.scalaz.concurrent.{Task => ZTask}                                                                 
                                                                                                                
                                                                                                                
object Task {                                                                                                   
                                                                                                                
  def fromScala[A]                    

non

package quantity

// like Nat, but for integers
trait Z

// Pos means positive-or-zero, and Neg means negative-or-zero
trait Pos extends Z { type P <: Pos } 
trait Neg extends Z { type N <: Neg } 

class Zero extends Pos with Neg { type N = Zero }

pchiusano

import scalaz.Applicative
import scalaz.concurrent.Task

/** 
 * This `Applicative[Task]` runs tasks in parallel, by defining
 * `ap` and `apply2` in terms of `mapBoth`. This differs from the
 *  default `Applicative[Task]`, where effects are sequenced 
 *  deterministically, in left to right order.
 */
val T = new Applicative[Task] {

sghike

// JVM sizing options
-server -Xms40g -Xmx40g -XX:MaxDirectMemorySize=4096m -XX:PermSize=256m -XX:MaxPermSize=256m   
// Young generation options
-XX:NewSize=6g -XX:MaxNewSize=6g -XX:+UseParNewGC -XX:MaxTenuringThreshold=2 -XX:SurvivorRatio=8 -XX:+UnlockDiagnosticVMOptions -XX:ParGCCardsPerStrideChunk=32768
// Old generation  options
-XX:+UseConcMarkSweepGC -XX:CMSParallelRemarkEnabled -XX:+ParallelRefProcEnabled -XX:+CMSClassUnloadingEnabled  -XX:CMSInitiatingOccupancyFraction=80 -XX:+UseCMSInitiatingOccupancyOnly   
// Other options
-XX:+AlwaysPreTouch -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintTenuringDistribution -XX:+PrintGCApplicationStoppedTime -XX:-OmitStackTraceInFastThrow

david-christiansen

module FizzBuzzC

%default total

-- Dependently typed FizzBuzz, constructively

-- A number is fizzy if it is evenly divisible by 3
data Fizzy : Nat -> Type where
  ZeroFizzy : Fizzy 0
  Fizz : Fizzy n -> Fizzy (3 + n)

nkpart

{-# LANGUAGE NoMonomorphismRestriction #-}
{-# LANGUAGE TemplateHaskell           #-}
{-# OPTIONS_GHC -fwarn-missing-methods #-}
module Err where

import Control.Lens
import Control.Monad.Error
import Control.Monad.Error.Lens

-- Here is a fairly typical situation, where we have low level errors in certain

djspiewak

Introduction to scalaz-stream

Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.

The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca

adeekshith

# <type>: (If applied, this commit will...) <subject> (Max 50 char)
# |<----  Using a Maximum Of 50 Characters  ---->|


# Explain why this change is being made
# |<----   Try To Limit Each Line to a Maximum Of 72 Characters   ---->|

# Provide links or keys to any relevant tickets, articles or other resources
# Example: Github issue #23

yellowflash

sealed trait RegExp {
  def isFinal:Boolean
  def acceptsEmpty:Boolean
  def shift(prev:Boolean, character:Char):RegExp
  def matches(str:String) =
    if(str.isEmpty) this.acceptsEmpty
    else str.foldLeft(this.shift(true, str.head))(_.shift(false,_)).isFinal
}

object Epsilon extends RegExp {